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An image processing pipeline for time-series of Chlamydomonas reinhardtii fluorescence photos

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Chlamy-IMPI

This repository contains the image processing and data analysis pipeline used to study photosynthesis in a large number of Chlamydomonas reinhardtii mutants under various growth conditions.

Note: this repository is still under development, so things might break and these instructions might be incomplete.

Image processing

1. Well segmentation

After setting up the environment (see below), download all image data from the google drive folder, located at: https://drive.google.com/drive/folders/1rU8VOIdwBuDX_N6MTn0Bg5SYYb-Ov8zv and place all .tif files in the data directory in this project. Then run the image processing pipeline:

python well_segmentation_preprocessing/main.py

This should store a bunch of .npy files in the output/well_segmentation_cache directory. Note- you can skip this step, and download the .npy files directly from a shared cache here: https://drive.google.com/drive/folders/1LB1znkc95zbgKAPVU2Rz4MMwbdcjtsBK

2. Database creation

Run

python database_creation/main.py

You can also skip this step, and download a pre-created database directly from this folder: https://drive.google.com/drive/folders/1hclnhGfkmy8Rh1l_703z4dsmeCx1DbVz

Note: see the file paths.py for where the code looks to read and write these file caches from.

Data analysis

Coming soon.

Poetry instructions:

First install poetry: https://python-poetry.org/docs/#installation

Next, install the dependencies and activate the virtual environment:

$ poetry install
$ poetry shell

Streamlit instructions:

$ poetry shell
$ streamlit run chlamy_impi/interactive.demo.py

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An image processing pipeline for time-series of Chlamydomonas reinhardtii fluorescence photos

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